DSPy Skills Collection

A comprehensive collection of AI-powered skills for programming and optimizing LLM applications using the DSPy framework. These skills enable you to move from manual prompt engineering to systematic, programmatic LLM development.

Version Compatibility: All skills target DSPy 3.1.2 (released January 19, 2026). All code examples and APIs have been verified against this version.

🎯 What is DSPy?

DSPy is a declarative framework that lets you program language models instead of prompting them. It provides:
- Modular architecture - Compose LLM programs from reusable components
- Automatic optimization - Tune prompts, examples, and weights algorithmically
- Self-improving pipelines - Systems that get better with data

📚 Skills Index

Optimizers

Pipelines & Components

Agent Development

Output Validation

Advanced Patterns

Debugging & Monitoring

🎯 Choosing the Right Optimizer

🔄 Typical Workflow

1. Design → Signature Designer - Define inputs/outputs
2. Build → RAG Pipeline or Agent Builder - Create your DSPy program
3. Validate → Output Refinement - Add constraints
4. Optimize → Choose optimizer based on your data
5. Evaluate → Evaluation Suite - Measure improvements
6. Debug → Debugging & Observability - Monitor performance
7. Deploy → Fine-tune Bootstrap - Optional production optimization

📖 Documentation

• DSPy Framework Guide - Complete framework reference

🚀 Installation

# Install DSPy 3.1.2 or later
pip install dspy-ai>=3.1.2

Optional Dependencies

# For ColBERTv2 retrieval
pip install colbert-ai

# For Haystack integration
pip install haystack-ai

# For fine-tuning
pip install transformers datasets

💡 Quick Start

import dspy

# Configure LM
dspy.configure(lm=dspy.LM("openai/gpt-4o-mini"))

# Create a simple classifier
classify = dspy.Predict("text -> sentiment: bool")
result = classify(text="I love this product!")
print(result.sentiment)  # True

📁 Examples

See examples/code-snippets.py for production-ready code.

🤝 Contributing

We welcome contributions! See CONTRIBUTING.md for guidelines.

📜 License

MIT License - see LICENSE for details.

🙏 Acknowledgments

Built for the SkillsMP marketplace. Uses the DSPy framework by Stanford NLP.